Changements de l’espérance de vie à la naissance pendant la pandémie de COVID-19 et contributions selon la cause de décès en Colombie-Britannique, Canada
Bibliographic record
Abstract
Des études ont démontré que la surmortalité, toutes causes confondues, pendant la pandémie de COVID 19 a entraîné une baisse de l’espérance de vie à la naissance dans la plupart des pays. Cette tendance renverse la vapeur, alors qu’une amélioration en ce sens avait été constatée au cours des décennies précédant la pandémie. Toutefois, ces études ne se sont que rarement penchées sur les facteurs qui ont contribué à des causes précises de décès autres que la COVID 19. La présente étude vise à quantifier les changements entre l’année 2019 et chaque année de pandémie, ainsi que les facteurs contributifs issus de la COVID 19, la toxicité des médicaments non réglementés et les autres causes de décès en Colombie-Britannique, au Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".